This page provides introductory information on the use of R in an introductory applied statistics class.
In particular, it provides:

An R package for introductory statistics (uwIntroStats),

An introduction to R (and the above package),

Some annotated examples of the use of specific functions from uwIntroStats,

Some video tutorials on the use of R to perform basic statistical analyses, and

A rough translation between Stata commands and R commands.

uwIntroStats

This is a package designed for introductory statistics students. It adds functionality to many R functions, in addition to streamlining
output and implementing many STATA functions in R. The package grew out of a desire for students in the introductory biostatistics courses at the
University of Washington to learn statistical analysis techniques using R. We believe that the output given by the package is more germane to
the problems most introductory students will face than that in the base R functions, or in many other packages.

The major changes in uwIntroStats are:

Making all types of regression (linear, generalized, proportional hazards, and corelated data) available in one function

Using robust standard error estimates (from the sandwich package) by default in regression and inference

Printing output in a much more intuitive manner

Upgrading the boxplot function to support stratification and the overlay of mean and standard deviation lines

Upgrading scatterplot functionality to support stratification and plotting loess and least squares lines

Allowing the user to specify multiple-partial F-tests within a regression call

Last, we present a document outlining our philosophy and approach to analyzing a data set, along with examples and code, titled Notes re: FEV. We analyze the FEV dataset, hosted on this website under the datasets page.
This analysis shows the typical process that Scott goes through in a quarter teaching Applied Biostatistics at the University of Washington.

All of the documents are presented again below. We also have some video tutorials on installing R and RStudio for Windows and Mac OS, using graphical user interfaces with R,
the R workspace and data frames, and an introductory video to the uwIntroStats package.